In [1]:
from gevi_classes import *
from paths import *
%matplotlib inline
%load_ext autoreload
%autoreload 2
import pandas as pd
import seaborn as sns
import statsmodels.formula.api as smf
from sklearn.linear_model import LinearRegression
from sklearn import metrics
from sklearn.cross_validation import train_test_split
import numpy as np
At Imperial
In [2]:
from IPython.display import set_matplotlib_formats
set_matplotlib_formats('jpeg')
%config InlineBackend.figure_format = 'jpeg'
%config InlineBackend.rc = {'font.size': 10, 'figure.figsize': (6.0, 4.0), \
                            'figure.facecolor': (1, 1, 1, 0), 'savefig.dpi': 36, \
                            'figure.subplot.bottom': 0.125, 'figure.edgecolor': (1, 1, 1, 0)}
In [3]:
%%javascript
IPython.OutputArea.auto_scroll_threshold = 100;
In [4]:
# instantiate utility class
gr = Graph()
In [5]:
# load data
mice = loadDataLight()
# loadMask(mice.mice)
mouseA
mouseB
mouseM1217F
mouseM1223M
In [6]:
gr.plotTF(mouseA, mask=True)
Out[6]:
1
In [7]:
gr.plotTF(mouseB, mask=False)
Out[7]:
1
In [8]:
gr.plotTF(mouseM1217F, mask=True)
Out[8]:
1
In [9]:
gr.plotTF(mouseM1223M, mask=True)
Out[9]:
1
In [ ]: